Hugging Face's logo

Spaces:
raoyonghui
/
maskgct
Runtime error

App Files Community
maskgct
File size: 4,883 Bytes 
c968fc3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
 
# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.

import os
import json
import librosa
from tqdm import tqdm
from glob import glob
from collections import defaultdict

from utils.util import has_existed


def get_lines(file):
    with open(file, "r") as f:
        lines = f.readlines()
        lines = [l.strip() for l in lines]
    return lines


def vctk_statistics(data_dir):
    speakers = []
    speakers2utts = defaultdict(list)

    speaker_infos = glob(data_dir + "/wav48_silence_trimmed" + "/*")

    for speaker_info in speaker_infos:
        speaker = speaker_info.split("/")[-1]

        if speaker == "log.txt":
            continue

        speakers.append(speaker)

        utts = glob(speaker_info + "/*")

        for utt in utts:
            uid = (
                utt.split("/")[-1].split("_")[1]
                + "_"
                + utt.split("/")[-1].split("_")[2].split(".")[0]
            )
            speakers2utts[speaker].append(uid)

    unique_speakers = list(set(speakers))
    unique_speakers.sort()

    print("Speakers: \n{}".format("\t".join(unique_speakers)))
    return speakers2utts, unique_speakers


def vctk_speaker_infos(data_dir):
    file = os.path.join(data_dir, "speaker-info.txt")
    lines = get_lines(file)

    ID2speakers = defaultdict()
    for l in tqdm(lines):
        items = l.replace(" ", "")

        if items[:2] == "ID":
            # The header line
            continue

        if items[0] == "p":
            id = items[:4]
            gender = items[6]
        elif items[0] == "s":
            id = items[:2]
            gender = items[4]

        if gender == "F":
            speaker = "female_{}".format(id)
        elif gender == "M":
            speaker = "male_{}".format(id)

        ID2speakers[id] = speaker

    return ID2speakers


def main(output_path, dataset_path, TEST_NUM_OF_EVERY_SPEAKER=3):
    print("-" * 10)
    print("Preparing test samples for vctk...")

    save_dir = os.path.join(output_path, "vctk")
    os.makedirs(save_dir, exist_ok=True)
    train_output_file = os.path.join(save_dir, "train.json")
    test_output_file = os.path.join(save_dir, "test.json")
    singer_dict_file = os.path.join(save_dir, "singers.json")
    utt2singer_file = os.path.join(save_dir, "utt2singer")
    if has_existed(train_output_file):
        return
    utt2singer = open(utt2singer_file, "w")

    # Load
    vctk_dir = dataset_path

    ID2speakers = vctk_speaker_infos(vctk_dir)
    speaker2utts, unique_speakers = vctk_statistics(vctk_dir)

    # We select speakers of standard samples as test utts
    train = []
    test = []

    train_index_count = 0
    test_index_count = 0
    test_speaker_count = defaultdict(int)

    train_total_duration = 0
    test_total_duration = 0

    for i, speaker in enumerate(speaker2utts.keys()):
        for chosen_uid in tqdm(
            speaker2utts[speaker],
            desc="Speaker {}/{}, #Train = {}, #Test = {}".format(
                i + 1, len(speaker2utts), train_index_count, test_index_count
            ),
        ):
            res = {
                "Dataset": "vctk",
                "Singer": ID2speakers[speaker],
                "Uid": "{}#{}".format(ID2speakers[speaker], chosen_uid),
            }
            res["Path"] = "{}/{}_{}.flac".format(speaker, speaker, chosen_uid)
            res["Path"] = os.path.join(vctk_dir, "wav48_silence_trimmed", res["Path"])
            assert os.path.exists(res["Path"])

            duration = librosa.get_duration(filename=res["Path"])
            res["Duration"] = duration

            if test_speaker_count[speaker] < TEST_NUM_OF_EVERY_SPEAKER:
                res["index"] = test_index_count
                test_total_duration += duration
                test.append(res)
                test_index_count += 1
                test_speaker_count[speaker] += 1
            else:
                res["index"] = train_index_count
                train_total_duration += duration
                train.append(res)
                train_index_count += 1

            utt2singer.write("{}\t{}\n".format(res["Uid"], res["Singer"]))

    print("#Train = {}, #Test = {}".format(len(train), len(test)))
    print(
        "#Train hours= {}, #Test hours= {}".format(
            train_total_duration / 3600, test_total_duration / 3600
        )
    )

    # Save train.json and test.json
    with open(train_output_file, "w") as f:
        json.dump(train, f, indent=4, ensure_ascii=False)
    with open(test_output_file, "w") as f:
        json.dump(test, f, indent=4, ensure_ascii=False)

    # Save singers.json
    singer_lut = {name: i for i, name in enumerate(unique_speakers)}
    with open(singer_dict_file, "w") as f:
        json.dump(singer_lut, f, indent=4, ensure_ascii=False)